Open Access
Issue |
ITM Web Conf.
Volume 21, 2018
Computing in Science and Technology (CST 2018)
|
|
---|---|---|
Article Number | 00002 | |
Number of page(s) | 9 | |
DOI | https://doi.org/10.1051/itmconf/20182100002 | |
Published online | 12 October 2018 |
- E. Dudek-Dyduch, Intelligent ALMM System for Discrete Optimization Problems – the Idea of Knowledge Base Application, ISAT, Vol. 657, (2017) [Google Scholar]
- E. Dudek-Dyduch, S. Korzonek: ALMM Solver for combinatorial and discrete optimization problems Idea of Problem Model Library, ACIIDS Part I. LNAI, vol. 9621, (2016) [Google Scholar]
- S. Korzonek, E. Dudek-Dyduch, Component Library of Problem Models for ALMM Solver, Journal of Information and Telecommunication, 1:3, pp. 224–240, (2017) [CrossRef] [Google Scholar]
- E. Dudek-Dyduch,: Modeling Manufacturing Processes with Disturbances a New Method Based on Algebraic-Logical Meta-Model. ICAISC, Part II. LNCS, vol. 9120, (2015) [Google Scholar]
- E. Dudek-Dyduch, E. Kucharska, L. Dutkiewicz, K. Rączka: ALMM Solver-A Tool for Optimization Problems. ICAISC 2014, pp. 328–338 (2014) [Google Scholar]
- E. Dudek-Dyduch, E. Kucharska: Learning method for co-operation. ICCCI 2011 Part II. LNCS, vol. 6923, pp. 290–300. Springer, Heidelberg, (2011) [Google Scholar]
- E. Dudek-Dyduch, L. Dutkiewicz: Substitution tasks method for discrete optimization. ICAISC 2013, Part II. LNCS, vol. 7895, pp. 419–430, (2013) [Google Scholar]
- E. Dudek-Dyduch, E. Kucharska: Optimization Learning Method for Discrete Process Control. In: ICINCO 2011, Vol. 1, pp. 24–33, (2011) [Google Scholar]
- E. Dudek-Dyduch, E. Kucharska, L. Dutkiewicz, K. Rączka: ALMM Solver-A Tool for Optimization Problems. ICAISC 2014, pp. 328–338, (2014) [Google Scholar]
- L. Dutkiewicz, E. Dudek-Dyduch: Substitution Tasks Method for Co-operation. In: Recent Developments in Computational Collective Intelligence, pp. 103–113, (2014) [CrossRef] [Google Scholar]
- E. Dudek-Dyduch: Learning based algorithm in scheduling. Journal of Intelligent Manufacturing (JIM), Vol. 11, no 2, pp. 135–143., (2000) [Google Scholar]
- E. Dudek-Dyduch,: Problems of knowledge representation in expert system aided control of DPP (in Polish), part I, pp. 147–154, Wrocław, (1993) [Google Scholar]
- E. Dudek-Dyduch,: Algebraic Logical Meta-Model of Decision Processes New Metaheuristics. ICAISC, Part 1. LNCS, vol. 9119, pp. 541–554, (2015) [Google Scholar]
- E. Dudek-Dyduch,: Modeling Manufacturing Processes with Disturbances – Two-Stage AL Model Transformation Method, MMAR, pp. 782–787 (2015) [Google Scholar]
- E. Dudek-Dyduch: Discrete determinable processes compact knowledge-based model, Notas de Matematica No 137, Universidad de Los Andes Venezuela, (1993) [Google Scholar]
- E. Dudek-Dyduch: Formalization and analysis of problems of discrete manufacturing processes. Scientific bulletin of AGH University, Automatics Vol. 54, (in Polish), (1990) [Google Scholar]
- K. Rączka, E. Dudek-Dyduch, E. Kucharska, L. Dutkiewicz: ALMM Solver: the Idea and the Architecture. In: Rutkowski at al. (Eds.) ICAISC 2015, Part II. LNCS, vol. 9120, pp. 504–514, Springer International Publishing, (2015) [Google Scholar]
- P. Jędrzejowicz, E. Ratajczak-Ropel: Reinforcement Learning Strategy for Solving the MRCPSP by a Team of Agents, Intelligent Decision Technologies, Smart Innovation, Systems and Technologies, Vol. 39, Springer, pp. 537–548, (2015) [CrossRef] [Google Scholar]
- E. Dudek-Dyduch: Information systems for production management (in Polish) Wyd. Poldex, Kraków ISBN 83-88979-12-4,(2002) [Google Scholar]
- L Anselma,. L. Piovesan, A. Sattar, B. Stantic, A. Paolo Terenzian, Comprehensive Approach to ‘Now’ in Temporal Relational Databases: Semantics and Representation, IEEE Transactions On Knowledge And Data Engineering, Vol.: 28, Issue: 10, pp: 2538–2551 [Google Scholar]
- E. Dudek-Dyduch, T. Dyduch: Formal approach to optimization of discrete manufacturing processes. in: Hamza, M.H. Proc. of the Twelfth IASTED, Acta Press, Zurich, (1993) [Google Scholar]
- F. Rossi, P. Van Beek, T. Walsh,: Handbook of Constraint Programming, Elsevier, (2006) [Google Scholar]
- P. Terenziani, Nearly Periodic Facts in Temporal Relational Databases, IEEE Transactions on Knowledge and Data Engineering, Volume: 28, Issue: 10, Pages: 2822–2826, (2016) [CrossRef] [Google Scholar]
- E. Kucharska, E. Dudek-Dyduch: Extended Learning Method for Designation of Cooperation. In: Transactions on Computational Collective Intelligence XIV, pp. 136–157, (2014) [Google Scholar]
- J. M. Medina, C. D. Barranco, O. Pons, Evaluation of Indexing Strategies for Possibilistic Queries Based on Indexing Techniques Available in Traditional RDBMS, (2016) [Google Scholar]
- F. Abdelhedi, A.A. Brahim, F. Atigui, G. Zurfluh, Big Data and Knowledge Management: How to Implement Conceptual Models in NoSQL Systems?, Knowledge Engineering And Knowledge Management, vol. 3 (KMIS), pp: 235–240, (2016) [Google Scholar]
- J Błażewicz., K. Ecker, E. Pesch, G. Schmidt, J. Węglarz: Handbook on Scheduling. Springer Berlin Heidelberg New York, ISBN 978-3-540-28046-0, (2007) [Google Scholar]
- R.E. Smith, N. Taylor: A Framework for Evolutionary Computation in Agent-Based Systems, Proc. of Int. Conf. on Intelligent Systems, pp. 221–224. 1SCA Press, (1998) [Google Scholar]
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